Overview

Dataset statistics

Number of variables16
Number of observations267
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory33.5 KiB
Average record size in memory128.5 B

Variable types

NUM16

Warnings

W_FEMALE is highly correlated with AA_FEMALE and 4 other fieldsHigh correlation
AA_FEMALE is highly correlated with W_FEMALE and 4 other fieldsHigh correlation
MALE is highly correlated with FEMALEHigh correlation
FEMALE is highly correlated with MALEHigh correlation
AA_MALE is highly correlated with AA_FEMALE and 4 other fieldsHigh correlation
W_MALE is highly correlated with AA_FEMALE and 4 other fieldsHigh correlation
H_MALE is highly correlated with H_Female and 1 other fieldsHigh correlation
H_Female is highly correlated with H_MALE and 1 other fieldsHigh correlation
AA is highly correlated with AA_FEMALE and 4 other fieldsHigh correlation
H is highly correlated with H_Female and 1 other fieldsHigh correlation
W is highly correlated with AA_FEMALE and 4 other fieldsHigh correlation
df_index has unique values Unique
ECONOMICALLY_DISADVANTAGED has unique values Unique
AA_MALE has unique values Unique
W_MALE has unique values Unique
AA has unique values Unique

Reproduction

Analysis started2020-11-09 18:20:43.116290
Analysis finished2020-11-09 18:21:25.214269
Duration42.1 seconds
Software versionpandas-profiling v2.9.0
Download configurationconfig.yaml

Variables

df_index
Real number (ℝ≥0)

UNIQUE

Distinct267
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean159.6816479
Minimum0
Maximum321
Zeros1
Zeros (%)0.4%
Memory size2.1 KiB
2020-11-09T12:21:25.317987image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile14.6
Q185
median158
Q3229.5
95-th percentile307.7
Maximum321
Range321
Interquartile range (IQR)144.5

Descriptive statistics

Standard deviation91.96640323
Coefficient of variation (CV)0.5759359602
Kurtosis-1.081885876
Mean159.6816479
Median Absolute Deviation (MAD)72
Skewness0.04716173297
Sum42635
Variance8457.819324
MonotocityStrictly increasing
2020-11-09T12:21:25.486990image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%) 
32110.4%
 
10410.4%
 
12010.4%
 
11910.4%
 
11810.4%
 
11710.4%
 
11610.4%
 
11510.4%
 
11410.4%
 
11310.4%
 
Other values (257)25796.3%
 
ValueCountFrequency (%) 
010.4%
 
110.4%
 
210.4%
 
310.4%
 
410.4%
 
ValueCountFrequency (%) 
32110.4%
 
32010.4%
 
31910.4%
 
31810.4%
 
31710.4%
 

grad_rate
Real number (ℝ≥0)

Distinct29
Distinct (%)10.9%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0.9171535581
Minimum0.64
Maximum0.99
Zeros0
Zeros (%)0.0%
Memory size2.1 KiB
2020-11-09T12:21:25.661990image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum0.64
5-th percentile0.773
Q10.9
median0.94
Q30.96
95-th percentile0.98
Maximum0.99
Range0.35
Interquartile range (IQR)0.06

Descriptive statistics

Standard deviation0.0663335359
Coefficient of variation (CV)0.07232544138
Kurtosis4.416105273
Mean0.9171535581
Median Absolute Deviation (MAD)0.03
Skewness-1.979519562
Sum244.88
Variance0.004400137985
MonotocityNot monotonic
2020-11-09T12:21:25.795108image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=29)
ValueCountFrequency (%) 
0.963312.4%
 
0.943212.0%
 
0.972710.1%
 
0.92259.4%
 
0.93207.5%
 
0.95186.7%
 
0.98186.7%
 
0.91155.6%
 
0.9124.5%
 
0.8893.4%
 
Other values (19)5821.7%
 
ValueCountFrequency (%) 
0.6420.7%
 
0.6510.4%
 
0.6610.4%
 
0.6920.7%
 
0.7220.7%
 
ValueCountFrequency (%) 
0.9983.0%
 
0.98186.7%
 
0.972710.1%
 
0.963312.4%
 
0.95186.7%
 

TOTAL
Real number (ℝ≥0)

Distinct248
Distinct (%)92.9%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean947.2059925
Minimum67
Maximum2411
Zeros0
Zeros (%)0.0%
Memory size2.1 KiB
2020-11-09T12:21:25.983113image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum67
5-th percentile283.4
Q1522
median833
Q31255.5
95-th percentile2070.4
Maximum2411
Range2344
Interquartile range (IQR)733.5

Descriptive statistics

Standard deviation548.8491366
Coefficient of variation (CV)0.5794401016
Kurtosis-0.1834135175
Mean947.2059925
Median Absolute Deviation (MAD)352
Skewness0.7583994564
Sum252904
Variance301235.3747
MonotocityNot monotonic
2020-11-09T12:21:26.171106image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%) 
75720.7%
 
48820.7%
 
84720.7%
 
83320.7%
 
83020.7%
 
70720.7%
 
81820.7%
 
40720.7%
 
131320.7%
 
91420.7%
 
Other values (238)24792.5%
 
ValueCountFrequency (%) 
6710.4%
 
7010.4%
 
7510.4%
 
8810.4%
 
10910.4%
 
ValueCountFrequency (%) 
241110.4%
 
232910.4%
 
229510.4%
 
228810.4%
 
228710.4%
 

ECONOMICALLY_DISADVANTAGED
Real number (ℝ≥0)

UNIQUE

Distinct267
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0.2966413681
Minimum0.007798440312
Maximum0.8259911894
Zeros0
Zeros (%)0.0%
Memory size2.1 KiB
2020-11-09T12:21:26.661004image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum0.007798440312
5-th percentile0.06907862408
Q10.2107418513
median0.2798264642
Q30.3682626054
95-th percentile0.5893400074
Maximum0.8259911894
Range0.8181927491
Interquartile range (IQR)0.1575207542

Descriptive statistics

Standard deviation0.1447872373
Coefficient of variation (CV)0.4880884897
Kurtosis1.593079635
Mean0.2966413681
Median Absolute Deviation (MAD)0.07982646421
Skewness0.8587220619
Sum79.20324527
Variance0.02096334409
MonotocityNot monotonic
2020-11-09T12:21:26.855952image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%) 
0.333333333310.4%
 
0.304195804210.4%
 
0.369109947610.4%
 
0.383863080710.4%
 
0.273447820310.4%
 
0.105110896810.4%
 
0.340425531910.4%
 
0.240190249710.4%
 
0.257894736810.4%
 
0.287356321810.4%
 
Other values (257)25796.3%
 
ValueCountFrequency (%) 
0.00779844031210.4%
 
0.0106681639510.4%
 
0.0155709342610.4%
 
0.0250696378810.4%
 
0.0286951813810.4%
 
ValueCountFrequency (%) 
0.825991189410.4%
 
0.786856127910.4%
 
0.766401590510.4%
 
0.730185497510.4%
 
0.709415584410.4%
 

FEMALE
Real number (ℝ≥0)

HIGH CORRELATION

Distinct263
Distinct (%)98.5%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0.4869020502
Minimum0.309352518
Maximum0.6666666667
Zeros0
Zeros (%)0.0%
Memory size2.1 KiB
2020-11-09T12:21:27.054951image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum0.309352518
5-th percentile0.4512847241
Q10.4711709114
median0.4846686449
Q30.4990381832
95-th percentile0.525574635
Maximum0.6666666667
Range0.3573141487
Interquartile range (IQR)0.02786727176

Descriptive statistics

Standard deviation0.03174991593
Coefficient of variation (CV)0.06520801446
Kurtosis11.20015327
Mean0.4869020502
Median Absolute Deviation (MAD)0.01416504778
Skewness0.9255173248
Sum130.0028474
Variance0.001008057162
MonotocityNot monotonic
2020-11-09T12:21:27.230947image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%) 
0.482142857131.1%
 
0.520.7%
 
0.521739130420.7%
 
0.522388059710.4%
 
0.475644699110.4%
 
0.456074766410.4%
 
0.471004243310.4%
 
0.442857142910.4%
 
0.485970819310.4%
 
0.521367521410.4%
 
Other values (253)25394.8%
 
ValueCountFrequency (%) 
0.30935251810.4%
 
0.376923076910.4%
 
0.395498392310.4%
 
0.432360742710.4%
 
0.438721136810.4%
 
ValueCountFrequency (%) 
0.666666666710.4%
 
0.645251396610.4%
 
0.634259259310.4%
 
0.596899224810.4%
 
0.590909090910.4%
 

H_Female
Real number (ℝ≥0)

HIGH CORRELATION

Distinct263
Distinct (%)98.5%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0.03632768463
Minimum0.002118644068
Maximum0.17114788
Zeros0
Zeros (%)0.0%
Memory size2.1 KiB
2020-11-09T12:21:27.402951image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum0.002118644068
5-th percentile0.005365477763
Q10.01353619339
median0.0250990753
Q30.04697363256
95-th percentile0.1111404831
Maximum0.17114788
Range0.169029236
Interquartile range (IQR)0.03343743917

Descriptive statistics

Standard deviation0.03455007583
Coefficient of variation (CV)0.9510673796
Kurtosis3.746723204
Mean0.03632768463
Median Absolute Deviation (MAD)0.01293362518
Skewness1.927885791
Sum9.699491797
Variance0.00119370774
MonotocityNot monotonic
2020-11-09T12:21:27.567948image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%) 
0.00375234521620.7%
 
0.00502512562820.7%
 
0.00990099009920.7%
 
0.0106100795820.7%
 
0.0079051383410.4%
 
0.128672745710.4%
 
0.0626878488610.4%
 
0.0176870748310.4%
 
0.067594433410.4%
 
0.00675675675710.4%
 
Other values (253)25394.8%
 
ValueCountFrequency (%) 
0.00211864406810.4%
 
0.00220264317210.4%
 
0.00227790432810.4%
 
0.00317460317510.4%
 
0.00375234521620.7%
 
ValueCountFrequency (%) 
0.1711478810.4%
 
0.169322709210.4%
 
0.163288940410.4%
 
0.161307053910.4%
 
0.156028368810.4%
 

AA_FEMALE
Real number (ℝ≥0)

HIGH CORRELATION

Distinct266
Distinct (%)99.6%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0.09856105154
Minimum0.000761614623
Maximum0.4991735537
Zeros0
Zeros (%)0.0%
Memory size2.1 KiB
2020-11-09T12:21:27.738952image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum0.000761614623
5-th percentile0.004414808682
Q10.0133601071
median0.03802938634
Q30.123181432
95-th percentile0.4113362163
Maximum0.4991735537
Range0.4984119391
Interquartile range (IQR)0.1098213249

Descriptive statistics

Standard deviation0.1280305032
Coefficient of variation (CV)1.298996928
Kurtosis1.764736264
Mean0.09856105154
Median Absolute Deviation (MAD)0.03010074412
Skewness1.681398458
Sum26.31580076
Variance0.01639180975
MonotocityNot monotonic
2020-11-09T12:21:27.904948image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%) 
0.0109890109920.7%
 
0.0111940298510.4%
 
0.408536585410.4%
 
0.0734522560310.4%
 
0.198324022310.4%
 
0.475770925110.4%
 
0.00142247510710.4%
 
0.0402298850610.4%
 
0.0205992509410.4%
 
0.0628722700210.4%
 
Other values (256)25695.9%
 
ValueCountFrequency (%) 
0.00076161462310.4%
 
0.00142247510710.4%
 
0.00196463654210.4%
 
0.00279069767410.4%
 
0.00297619047610.4%
 
ValueCountFrequency (%) 
0.499173553710.4%
 
0.480607082610.4%
 
0.475770925110.4%
 
0.474452554710.4%
 
0.473360655710.4%
 

W_FEMALE
Real number (ℝ≥0)

HIGH CORRELATION

Distinct266
Distinct (%)99.6%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0.3410001682
Minimum0.001776198934
Maximum0.6
Zeros0
Zeros (%)0.0%
Memory size2.1 KiB
2020-11-09T12:21:28.087951image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum0.001776198934
5-th percentile0.0137908778
Q10.2807330732
median0.3913924051
Q30.4439639946
95-th percentile0.4700716309
Maximum0.6
Range0.5982238011
Interquartile range (IQR)0.1632309214

Descriptive statistics

Standard deviation0.1410781168
Coefficient of variation (CV)0.4137186136
Kurtosis0.3064158766
Mean0.3410001682
Median Absolute Deviation (MAD)0.05987878138
Skewness-1.181485424
Sum91.04704491
Variance0.01990303504
MonotocityNot monotonic
2020-11-09T12:21:28.251948image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%) 
0.444444444420.7%
 
0.458333333310.4%
 
0.441860465110.4%
 
0.39902676410.4%
 
0.377289377310.4%
 
0.266409266410.4%
 
0.351648351610.4%
 
0.0366013071910.4%
 
0.0278699402810.4%
 
0.422314049610.4%
 
Other values (256)25695.9%
 
ValueCountFrequency (%) 
0.00177619893410.4%
 
0.00191570881210.4%
 
0.00220264317210.4%
 
0.00330578512410.4%
 
0.00335008375210.4%
 
ValueCountFrequency (%) 
0.610.4%
 
0.53703703710.4%
 
0.519480519510.4%
 
0.511363636410.4%
 
0.494565217410.4%
 

MALE
Real number (ℝ≥0)

HIGH CORRELATION

Distinct263
Distinct (%)98.5%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0.5130979498
Minimum0.3333333333
Maximum0.690647482
Zeros0
Zeros (%)0.0%
Memory size2.1 KiB
2020-11-09T12:21:28.433950image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum0.3333333333
5-th percentile0.474425365
Q10.5009618168
median0.5153313551
Q30.5288290886
95-th percentile0.5487152759
Maximum0.690647482
Range0.3573141487
Interquartile range (IQR)0.02786727176

Descriptive statistics

Standard deviation0.03174991593
Coefficient of variation (CV)0.06187885948
Kurtosis11.20015327
Mean0.5130979498
Median Absolute Deviation (MAD)0.01416504778
Skewness-0.9255173248
Sum136.9971526
Variance0.001008057162
MonotocityNot monotonic
2020-11-09T12:21:28.602952image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%) 
0.517857142931.1%
 
0.520.7%
 
0.478260869620.7%
 
0.477611940310.4%
 
0.494939271310.4%
 
0.534883720910.4%
 
0.551515151510.4%
 
0.508534850610.4%
 
0.494932432410.4%
 
0.512485136710.4%
 
Other values (253)25394.8%
 
ValueCountFrequency (%) 
0.333333333310.4%
 
0.354748603410.4%
 
0.365740740710.4%
 
0.403100775210.4%
 
0.409090909110.4%
 
ValueCountFrequency (%) 
0.69064748210.4%
 
0.623076923110.4%
 
0.604501607710.4%
 
0.567639257310.4%
 
0.561278863210.4%
 

AA_MALE
Real number (ℝ≥0)

HIGH CORRELATION
UNIQUE

Distinct267
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0.09829004423
Minimum0.001715265866
Maximum0.5044052863
Zeros0
Zeros (%)0.0%
Memory size2.1 KiB
2020-11-09T12:21:28.757123image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum0.001715265866
5-th percentile0.004799809028
Q10.01596863645
median0.04444444444
Q30.1277951074
95-th percentile0.3965589714
Maximum0.5044052863
Range0.5026900205
Interquartile range (IQR)0.1118264709

Descriptive statistics

Standard deviation0.1244815951
Coefficient of variation (CV)1.266472063
Kurtosis1.80429017
Mean0.09829004423
Median Absolute Deviation (MAD)0.03424036281
Skewness1.673809331
Sum26.24344181
Variance0.01549566752
MonotocityNot monotonic
2020-11-09T12:21:28.933590image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%) 
0.00932835820910.4%
 
0.0801644398810.4%
 
0.0101246105910.4%
 
0.00761035007610.4%
 
0.0105820105810.4%
 
0.0101351351410.4%
 
0.0157303370810.4%
 
0.00246305418710.4%
 
0.00201207243510.4%
 
0.197707736410.4%
 
Other values (257)25796.3%
 
ValueCountFrequency (%) 
0.00171526586610.4%
 
0.00186915887910.4%
 
0.00201207243510.4%
 
0.00211864406810.4%
 
0.00225225225210.4%
 
ValueCountFrequency (%) 
0.504405286310.4%
 
0.502664298410.4%
 
0.470779220810.4%
 
0.469262295110.4%
 
0.460370994910.4%
 

W_MALE
Real number (ℝ≥0)

HIGH CORRELATION
UNIQUE

Distinct267
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0.3638259282
Minimum0.002994011976
Maximum0.5466237942
Zeros0
Zeros (%)0.0%
Memory size2.1 KiB
2020-11-09T12:21:29.107594image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum0.002994011976
5-th percentile0.02343597263
Q10.2985623521
median0.4194444444
Q30.46965415
95-th percentile0.5052575377
Maximum0.5466237942
Range0.5436297822
Interquartile range (IQR)0.1710917979

Descriptive statistics

Standard deviation0.1457406886
Coefficient of variation (CV)0.4005780713
Kurtosis0.3953528951
Mean0.3638259282
Median Absolute Deviation (MAD)0.06383581033
Skewness-1.219270557
Sum97.14152282
Variance0.02124034831
MonotocityNot monotonic
2020-11-09T12:21:29.277522image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%) 
0.472222222210.4%
 
0.0134099616910.4%
 
0.410826486210.4%
 
0.450980392210.4%
 
0.489320388310.4%
 
0.492346938810.4%
 
0.45743329110.4%
 
0.00426829268310.4%
 
0.437450199210.4%
 
0.0366013071910.4%
 
Other values (257)25796.3%
 
ValueCountFrequency (%) 
0.00299401197610.4%
 
0.00383141762510.4%
 
0.00426829268310.4%
 
0.00440528634410.4%
 
0.00502512562810.4%
 
ValueCountFrequency (%) 
0.546623794210.4%
 
0.524074074110.4%
 
0.522222222210.4%
 
0.520418848210.4%
 
0.518010291610.4%
 

H_MALE
Real number (ℝ≥0)

HIGH CORRELATION

Distinct263
Distinct (%)98.5%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0.03996564158
Minimum0.001860465116
Maximum0.1933815926
Zeros0
Zeros (%)0.0%
Memory size2.1 KiB
2020-11-09T12:21:29.449397image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum0.001860465116
5-th percentile0.007035006218
Q10.01541100409
median0.02572347267
Q30.04689070382
95-th percentile0.1192649089
Maximum0.1933815926
Range0.1915211274
Interquartile range (IQR)0.03147969973

Descriptive statistics

Standard deviation0.03802549281
Coefficient of variation (CV)0.951454582
Kurtosis3.665872705
Mean0.03996564158
Median Absolute Deviation (MAD)0.01378079751
Skewness1.924442604
Sum10.6708263
Variance0.001445938103
MonotocityNot monotonic
2020-11-09T12:21:29.612915image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%) 
0.0227272727331.1%
 
0.0219780219820.7%
 
0.0202702702720.7%
 
0.119402985110.4%
 
0.0524499654910.4%
 
0.0512820512810.4%
 
0.0363997352710.4%
 
0.0127118644110.4%
 
0.0108303249110.4%
 
0.118942731310.4%
 
Other values (253)25394.8%
 
ValueCountFrequency (%) 
0.00186046511610.4%
 
0.00237529691210.4%
 
0.00315457413210.4%
 
0.00375234521610.4%
 
0.0039525691710.4%
 
ValueCountFrequency (%) 
0.193381592610.4%
 
0.187739463610.4%
 
0.178423236510.4%
 
0.17834394910.4%
 
0.174940898310.4%
 

AA
Real number (ℝ≥0)

HIGH CORRELATION
UNIQUE

Distinct267
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0.1968510958
Minimum0.005145797599
Maximum0.9801762115
Zeros0
Zeros (%)0.0%
Memory size2.1 KiB
2020-11-09T12:21:29.813924image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum0.005145797599
5-th percentile0.00978701994
Q10.03110227261
median0.08121019108
Q30.2461306598
95-th percentile0.823879973
Maximum0.9801762115
Range0.9750304139
Interquartile range (IQR)0.2150283872

Descriptive statistics

Standard deviation0.2514253113
Coefficient of variation (CV)1.277236026
Kurtosis1.723118367
Mean0.1968510958
Median Absolute Deviation (MAD)0.06234226655
Skewness1.66703992
Sum52.55924257
Variance0.06321468715
MonotocityNot monotonic
2020-11-09T12:21:29.991930image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%) 
0.00694444444410.4%
 
0.0560420315210.4%
 
0.0683918669110.4%
 
0.0202702702710.4%
 
0.0225140712910.4%
 
0.0389873417710.4%
 
0.0599793174810.4%
 
0.0339832869110.4%
 
0.0579591836710.4%
 
0.0343878954610.4%
 
Other values (257)25796.3%
 
ValueCountFrequency (%) 
0.00514579759910.4%
 
0.00560747663610.4%
 
0.00568990042710.4%
 
0.00609291698410.4%
 
0.00671140939610.4%
 
ValueCountFrequency (%) 
0.980176211510.4%
 
0.945454545510.4%
 
0.942622950810.4%
 
0.940978077610.4%
 
0.928209459510.4%
 

H
Real number (ℝ≥0)

HIGH CORRELATION

Distinct265
Distinct (%)99.3%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0.07629332621
Minimum0.007125890736
Maximum0.3645294726
Zeros0
Zeros (%)0.0%
Memory size2.1 KiB
2020-11-09T12:21:30.176322image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum0.007125890736
5-th percentile0.01422568886
Q10.02926154565
median0.0509383378
Q30.09067816295
95-th percentile0.2318601733
Maximum0.3645294726
Range0.3574035819
Interquartile range (IQR)0.0614166173

Descriptive statistics

Standard deviation0.07177226387
Coefficient of variation (CV)0.9407410508
Kurtosis3.812364666
Mean0.07629332621
Median Absolute Deviation (MAD)0.02642220877
Skewness1.954906438
Sum20.3703181
Variance0.005151257861
MonotocityNot monotonic
2020-11-09T12:21:30.351323image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%) 
0.0204081632720.7%
 
0.0270270270320.7%
 
0.0503731343310.4%
 
0.0236486486510.4%
 
0.0205549845810.4%
 
0.0738963531710.4%
 
0.180613668110.4%
 
0.0568862275410.4%
 
0.129629629610.4%
 
0.0460829493110.4%
 
Other values (255)25595.5%
 
ValueCountFrequency (%) 
0.00712589073610.4%
 
0.00750469043210.4%
 
0.00911161731210.4%
 
0.00924702774110.4%
 
0.00952380952410.4%
 
ValueCountFrequency (%) 
0.364529472610.4%
 
0.342911877410.4%
 
0.341632889410.4%
 
0.339730290510.4%
 
0.330969267110.4%
 

W
Real number (ℝ≥0)

HIGH CORRELATION

Distinct266
Distinct (%)99.6%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0.7048260964
Minimum0.005747126437
Maximum0.9753694581
Zeros0
Zeros (%)0.0%
Memory size2.1 KiB
2020-11-09T12:21:30.540731image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum0.005747126437
5-th percentile0.04081219168
Q10.5893398787
median0.8169761273
Q30.9137326023
95-th percentile0.9610513934
Maximum0.9753694581
Range0.9696223317
Interquartile range (IQR)0.3243927236

Descriptive statistics

Standard deviation0.2821088473
Coefficient of variation (CV)0.4002531245
Kurtosis0.4841737248
Mean0.7048260964
Median Absolute Deviation (MAD)0.1127290881
Skewness-1.289871136
Sum188.1885677
Variance0.07958540171
MonotocityNot monotonic
2020-11-09T12:21:30.720738image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%) 
0.946428571420.7%
 
0.912313432810.4%
 
0.122887864810.4%
 
0.966666666710.4%
 
0.865051903110.4%
 
0.91455696210.4%
 
0.903881700610.4%
 
0.627565982410.4%
 
0.722811671110.4%
 
0.91122715410.4%
 
Other values (256)25695.9%
 
ValueCountFrequency (%) 
0.00574712643710.4%
 
0.00660792951510.4%
 
0.0083752093810.4%
 
0.00898203592810.4%
 
0.00914634146310.4%
 
ValueCountFrequency (%) 
0.975369458110.4%
 
0.971496437110.4%
 
0.969849246210.4%
 
0.96822033910.4%
 
0.967250571210.4%
 

Expend_per_pupil
Real number (ℝ≥0)

Distinct266
Distinct (%)99.6%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean9684.601348
Minimum5304.33
Maximum20356.1
Zeros0
Zeros (%)0.0%
Memory size2.1 KiB
2020-11-09T12:21:30.860914image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum5304.33
5-th percentile7688.027
Q18401.245
median9165.83
Q310528.48
95-th percentile12926.907
Maximum20356.1
Range15051.77
Interquartile range (IQR)2127.235

Descriptive statistics

Standard deviation2077.675623
Coefficient of variation (CV)0.2145339336
Kurtosis8.260019884
Mean9684.601348
Median Absolute Deviation (MAD)885.87
Skewness2.227728413
Sum2585788.56
Variance4316735.993
MonotocityNot monotonic
2020-11-09T12:21:31.017171image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%) 
5449.5920.7%
 
10789.4310.4%
 
9136.4310.4%
 
12407.3710.4%
 
8364.2510.4%
 
8652.2210.4%
 
11513.8510.4%
 
9016.7510.4%
 
8696.5610.4%
 
8266.1310.4%
 
Other values (256)25695.9%
 
ValueCountFrequency (%) 
5304.3310.4%
 
5449.5920.7%
 
5541.1410.4%
 
6949.9910.4%
 
7273.610.4%
 
ValueCountFrequency (%) 
20356.110.4%
 
20187.7910.4%
 
20049.1310.4%
 
18582.4510.4%
 
18237.5810.4%
 

Interactions

2020-11-09T12:20:46.279292image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-09T12:20:46.455286image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-09T12:20:46.619286image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-09T12:20:46.759289image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-09T12:20:46.905289image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-09T12:20:47.054288image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-09T12:20:47.198286image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-09T12:20:47.336286image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-09T12:20:47.488289image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-09T12:20:47.647292image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-09T12:20:47.796293image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-09T12:20:47.946295image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-09T12:20:48.111357image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-09T12:20:48.282363image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-09T12:20:48.463369image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-09T12:20:48.614364image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-09T12:20:48.793359image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-09T12:20:48.964362image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-09T12:20:49.133357image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-09T12:20:49.401360image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-09T12:20:49.570371image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-09T12:20:49.750356image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-09T12:20:49.935361image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-09T12:20:50.102356image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-09T12:20:50.278363image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-09T12:20:50.461359image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-09T12:20:50.640359image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-09T12:20:50.813634image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-09T12:20:50.992629image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-09T12:20:51.142634image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-09T12:20:51.344629image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-09T12:20:51.509668image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-09T12:20:51.691660image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-09T12:20:51.846665image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-09T12:20:51.999706image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-09T12:20:52.142745image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-09T12:20:52.286755image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-09T12:20:52.411296image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-09T12:20:52.551926image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-09T12:20:52.708880image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-09T12:20:52.849551image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-09T12:20:52.990179image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-09T12:20:53.099552image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-09T12:20:53.229262image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-09T12:20:53.371039image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-09T12:20:53.495363image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-09T12:20:53.635990image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-09T12:20:53.760989image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-09T12:20:53.894001image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-09T12:20:54.019001image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-09T12:20:54.144001image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-09T12:20:54.392163image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-09T12:20:54.534170image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-09T12:20:54.681459image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-09T12:20:54.838295image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-09T12:20:54.967525image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-09T12:20:55.092524image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-09T12:20:55.217527image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-09T12:20:55.364341image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-09T12:20:55.508352image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-09T12:20:55.647882image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-09T12:20:55.772881image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-09T12:20:55.924111image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-09T12:20:56.068111image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-09T12:20:56.197290image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-09T12:20:56.349408image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-09T12:20:56.498364image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-09T12:20:56.638996image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-09T12:20:56.763996image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-09T12:20:56.920241image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-09T12:20:57.076490image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-09T12:20:57.201489image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-09T12:20:57.343259image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-09T12:20:57.483880image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-09T12:20:57.635020image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-09T12:20:57.760014image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-09T12:20:57.916265image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-09T12:20:58.056892image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-09T12:20:58.213142image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-09T12:20:58.353768image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-09T12:20:58.494390image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-09T12:20:58.635020image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-09T12:20:58.791265image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-09T12:20:58.916274image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-09T12:20:59.056899image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-09T12:20:59.213143image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-09T12:20:59.369390image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-09T12:20:59.517378image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-09T12:20:59.658006image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-09T12:20:59.798628image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-09T12:20:59.923628image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-09T12:21:00.220505image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-09T12:21:00.376762image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-09T12:21:00.517382image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-09T12:21:00.658003image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-09T12:21:00.783005image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-09T12:21:00.939256image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-09T12:21:01.064258image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-09T12:21:01.204881image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-09T12:21:01.329881image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-09T12:21:01.454878image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-09T12:21:01.595502image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-09T12:21:01.736131image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-09T12:21:01.861133image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-09T12:21:01.986127image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-09T12:21:02.126755image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-09T12:21:02.251753image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-09T12:21:02.376759image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-09T12:21:02.517379image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-09T12:21:02.642386image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-09T12:21:02.767377image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-09T12:21:02.892380image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-09T12:21:03.033006image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-09T12:21:03.174110image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-09T12:21:03.317948image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-09T12:21:03.444587image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-09T12:21:03.582580image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-09T12:21:03.707583image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-09T12:21:03.848208image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-09T12:21:03.973207image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-09T12:21:04.113833image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-09T12:21:04.254458image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-09T12:21:04.379456image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-09T12:21:04.505631image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-09T12:21:04.661876image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-09T12:21:04.786878image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-09T12:21:04.927504image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-09T12:21:05.068136image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-09T12:21:05.193135image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-09T12:21:05.349383image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-09T12:21:05.490011image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-09T12:21:05.630628image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-09T12:21:05.755628image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-09T12:21:05.911883image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-09T12:21:06.052508image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-09T12:21:06.193130image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-09T12:21:06.333757image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-09T12:21:06.474377image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-09T12:21:06.615006image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-09T12:21:06.740008image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-09T12:21:07.124298image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-09T12:21:07.272269image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-09T12:21:07.422443image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-09T12:21:07.561720image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-09T12:21:07.723315image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-09T12:21:07.855119image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-09T12:21:07.995746image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-09T12:21:08.105117image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-09T12:21:08.230119image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-09T12:21:08.370747image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-09T12:21:08.520627image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-09T12:21:08.645631image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-09T12:21:08.800511image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-09T12:21:08.965516image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-09T12:21:09.112511image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-09T12:21:09.263517image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-09T12:21:09.416513image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-09T12:21:09.539934image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-09T12:21:09.664931image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-09T12:21:09.789936image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-09T12:21:09.930559image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-09T12:21:10.096716image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-09T12:21:10.245716image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-09T12:21:10.357141image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-09T12:21:10.482146image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-09T12:21:10.716880image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-09T12:21:10.864882image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-09T12:21:11.004874image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-09T12:21:11.153874image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-09T12:21:11.297233image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-09T12:21:11.427212image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-09T12:21:11.552218image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-09T12:21:11.692835image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-09T12:21:11.817833image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-09T12:21:11.958468image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-09T12:21:12.083461image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-09T12:21:12.252032image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-09T12:21:12.440410image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-09T12:21:12.645185image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-09T12:21:12.799012image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-09T12:21:12.946098image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-09T12:21:13.111909image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-09T12:21:13.268157image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-09T12:21:13.424671image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-09T12:21:13.574728image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-09T12:21:13.728099image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-09T12:21:13.878100image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-09T12:21:14.045198image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-09T12:21:14.219985image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-09T12:21:14.373469image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-09T12:21:14.535474image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-09T12:21:14.701468image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-09T12:21:14.882478image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-09T12:21:15.080475image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-09T12:21:15.271469image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-09T12:21:15.417468image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-09T12:21:15.564473image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-09T12:21:15.756469image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-09T12:21:15.958468image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-09T12:21:16.099469image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-09T12:21:16.466397image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-09T12:21:16.591390image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-09T12:21:16.716396image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-09T12:21:16.841391image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-09T12:21:16.995816image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-09T12:21:17.135858image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-09T12:21:17.282678image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-09T12:21:17.413128image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-09T12:21:17.564130image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-09T12:21:17.729131image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-09T12:21:17.903127image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-09T12:21:18.069130image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-09T12:21:18.217128image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-09T12:21:18.364045image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-09T12:21:18.508560image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-09T12:21:18.633562image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-09T12:21:18.789816image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-09T12:21:18.930442image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-09T12:21:19.071063image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-09T12:21:19.211689image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-09T12:21:19.367937image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-09T12:21:19.494074image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-09T12:21:19.634699image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-09T12:21:19.775330image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-09T12:21:19.950147image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-09T12:21:20.134894image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-09T12:21:20.282073image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-09T12:21:20.418690image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-09T12:21:20.562689image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-09T12:21:20.703662image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-09T12:21:20.854563image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-09T12:21:20.979568image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-09T12:21:21.119329image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-09T12:21:21.244323image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-09T12:21:21.369324image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-09T12:21:21.509945image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-09T12:21:21.654099image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-09T12:21:21.779105image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-09T12:21:21.930500image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-09T12:21:22.071553image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-09T12:21:22.196554image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-09T12:21:22.352804image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-09T12:21:22.509051image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-09T12:21:22.649686image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-09T12:21:22.774677image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-09T12:21:22.930936image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-09T12:21:23.087179image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-09T12:21:23.227804image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-09T12:21:23.381888image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-09T12:21:23.539002image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-09T12:21:23.666041image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-09T12:21:23.806667image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-09T12:21:23.962920image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-09T12:21:24.103546image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-09T12:21:24.259794image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-09T12:21:24.384792image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Correlations

2020-11-09T12:21:31.179664image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Pearson's r

The Pearson's correlation coefficient (r) is a measure of linear correlation between two variables. It's value lies between -1 and +1, -1 indicating total negative linear correlation, 0 indicating no linear correlation and 1 indicating total positive linear correlation. Furthermore, r is invariant under separate changes in location and scale of the two variables, implying that for a linear function the angle to the x-axis does not affect r.

To calculate r for two variables X and Y, one divides the covariance of X and Y by the product of their standard deviations.
2020-11-09T12:21:31.480631image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Spearman's ρ

The Spearman's rank correlation coefficient (ρ) is a measure of monotonic correlation between two variables, and is therefore better in catching nonlinear monotonic correlations than Pearson's r. It's value lies between -1 and +1, -1 indicating total negative monotonic correlation, 0 indicating no monotonic correlation and 1 indicating total positive monotonic correlation.

To calculate ρ for two variables X and Y, one divides the covariance of the rank variables of X and Y by the product of their standard deviations.
2020-11-09T12:21:31.824936image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Kendall's τ

Similarly to Spearman's rank correlation coefficient, the Kendall rank correlation coefficient (τ) measures ordinal association between two variables. It's value lies between -1 and +1, -1 indicating total negative correlation, 0 indicating no correlation and 1 indicating total positive correlation.

To calculate τ for two variables X and Y, one determines the number of concordant and discordant pairs of observations. τ is given by the number of concordant pairs minus the discordant pairs divided by the total number of pairs.
2020-11-09T12:21:32.133105image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Phik (φk)

Phik (φk) is a new and practical correlation coefficient that works consistently between categorical, ordinal and interval variables, captures non-linear dependency and reverts to the Pearson correlation coefficient in case of a bivariate normal input distribution. There is extensive documentation available here.

Missing values

2020-11-09T12:21:24.683018image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-09T12:21:25.042400image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Sample

First rows

df_indexgrad_rateTOTALECONOMICALLY_DISADVANTAGEDFEMALEH_FemaleAA_FEMALEW_FEMALEMALEAA_MALEW_MALEH_MALEAAHWExpend_per_pupil
000.9610750.2474420.4827910.0083720.0027910.4651160.5172090.0074420.5004650.0018600.0102330.0102330.9655819171.37
110.9511200.3392860.4517860.0107140.0205360.4098210.5482140.0196430.5053570.0160710.0401790.0267860.9151799523.76
220.9214060.1998580.4914650.0440970.0704130.3513510.5085350.0853490.3463730.0469420.1557610.0910380.69772412546.31
330.984810.1933470.4428270.0374220.0166320.3825360.5571730.0270270.4823280.0374220.0436590.0748440.8648659106.97
440.8915060.3718460.4907040.1693230.0863210.2284200.5092960.0830010.2556440.1606910.1693230.3300130.4840647418.07
550.915340.2378280.4887640.0561800.0205990.4082400.5112360.0224720.4232210.0599250.0430710.1161050.8314618279.85
660.946370.3265310.4866560.0062790.0109890.4615380.5133440.0282570.4631080.0125590.0392460.0188380.9246479673.19
770.935150.3864080.4485440.0213590.0097090.4155340.5514560.0077670.4893200.0388350.0174760.0601940.90485410027.42
880.9313960.2077360.4935530.0358170.0093120.4376790.5064470.0143270.4491400.0336680.0236390.0694840.8868199268.68
990.9316670.1511700.4997000.0173970.0083980.4691060.5003000.0173970.4571090.0185960.0257950.0359930.9262158945.95

Last rows

df_indexgrad_rateTOTALECONOMICALLY_DISADVANTAGEDFEMALEH_FemaleAA_FEMALEW_FEMALEMALEAA_MALEW_MALEH_MALEAAHWExpend_per_pupil
2573120.9418470.0286950.5175960.0454790.0270710.4141850.4824040.0216570.4001080.0443960.0487280.0898750.8142938335.75
2583130.981660.0602410.5421690.0361450.0120480.4638550.4578310.0240960.3915660.0240960.0361450.0602410.85542211230.73
2593140.9710820.0323480.4796670.0268020.0304990.3881700.5203330.0378930.4066540.0351200.0683920.0619220.7948248390.27
2603150.9816670.0077980.5176960.0209960.0323940.3713260.4823040.0341930.3491300.0257950.0665870.0467910.7204567977.52
2613160.9615330.0450100.4964120.0430530.0293540.4005220.5035880.0254400.4266140.0358770.0547950.0789300.8271368346.05
2623170.9418950.2474930.4860160.0585750.0781000.3356200.5139840.0796830.3620050.0638520.1577840.1224270.6976257842.51
2633180.9722200.0711710.4878380.0180180.0445950.4072070.5121620.0504500.4202700.0247750.0950450.0427930.8274777519.21
2643190.965710.1856390.4605950.0052540.0210160.4325740.5394050.0350260.4763570.0210160.0560420.0262700.90893210360.40
2653200.9719350.1090440.4739020.0273900.0506460.3757110.5260980.0470280.4304910.0335920.0976740.0609820.8062027995.72
2663210.94750.1200000.6666670.0266670.0133330.6000000.3333330.0133330.2933330.0133330.0266670.0400000.89333320049.13